Senior Data Scientist - Copilot Insights at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Feb, 26

Salary

0.0

Posted On

27 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Large Language Models, Statistical Techniques, AI Applications, Generative AI, Technical Leadership, Evaluation Frameworks, Product Development, Experimentation Systems, Business Objectives, Model Effectiveness, Communication, Innovation, Data Management, Transformer Models, Machine Learning

Industry

Software Development

Description

Responsibilities include defining Copilot metrics, supporting experimentation systems, and developing evaluation frameworks for Copilot investments. Develops extensive knowledge in the domain and technical framework, notably in Large Language Models (LLM), plays a role in advancing product development through ongoing awareness of industry trends and technologies, and continuously finding insights that drive product investment decisions. Assesses business needs and integrates research to achieve business objectives. This role involves guiding the selection of data to address issues strategically, leveraging knowledge to design, measure and build AI applications to drive tangible business results. Records ongoing work and experimental findings, sharing them to encourage innovation. Assesses the effectiveness of models and collaborates with product teams to design AI-driven experiences. Communicates and educates team members (engineers, product managers, leadership) on Data Science principles and methodologies so that they understand the models being built, conclusions being drawn, why the model was chosen, and how to interpret the results. Applies concepts to practical models and innovate at the speed of our business. It is critical that we ship models and enhancements on an on-going basis to empower us and our partners to focus our Copilot efforts across Office. Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) These requirements include but are not limited to the following specialized security screenings: Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. 4+ years of technical leadership in designing and scaling generative AI pipelines (retrieval augmented generation (RAG), finetuning, evaluation frameworks), with deep knowledge in transformer models and architectures. 1+ year experience building generative AI applications.

Responsibilities

Define Copilot metrics, support experimentation systems, and develop evaluation frameworks for Copilot investments. Collaborate with product teams to design AI-driven experiences and communicate Data Science principles to team members.